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Special Issue Information

Dear Colleagues,

This special issue presents the results of approximately 20 new studies on energy return on investment, including 10 empirical studies of particular energy resources and a similar number examining methodological issues and the social and economic implications of changing EROIs. The studies cover the most important energy resources currently used by Western society, as well as several possible alternatives. The results, which have great consistency across studies, have enormous implications for our economies and for society more generally. Several papers examine the direct economic and psychological implications of declining EROI, as well as the implications for planning. We believe that taken as a whole these papers have great power in helping to understand our current economic difficulties as well as guiding what we must do to adjust to new energy realities. A failure to understand these issues will severely limit our ability to plan for the future.

This paper is a synthesis of a series of twenty papers on the topic of EROI, or energy return on investment. EROI is simply the energy gained from an energy-obtaining effort divided by the energy used to get that energy. For example, one

This paper is a synthesis of a series of twenty papers on the topic of EROI, or energy return on investment. EROI is simply the energy gained from an energy-obtaining effort divided by the energy used to get that energy. For example, one barrel of oil invested into getting oil out of the ground might return fifty, thirty, ten or one barrel, depending when and where the process is taking place. It is meant to be read in conjunction with the first paper in this special issue and also a number of the papers themselves. As such I try to summarize what general trends we might conclude from these varied and often highly technical papers. About half of the papers are reports on empirical analyses of various energy sources such as Norwegian or Gulf of Mexico oil, Pennsylvania gas and so on. About a quarter of the papers are methodological: how do we go about undertaking these analyses, what problems are there, what are the proper boundaries and so on. The final quarter are in a sense philosophical: since it appears that we will be living indefinitely in a world of decreasing EROIs, what are the economic, social and psychological implications? The rest of this paper summarizes the results of these studies.
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Energy Return on Investment (EROI) refers to how much energy is returned from one unit of energy invested in an energy-producing activity. It is a critical parameter for understanding and ranking different fuels. There were a number of studies on EROI three decades

Energy Return on Investment (EROI) refers to how much energy is returned from one unit of energy invested in an energy-producing activity. It is a critical parameter for understanding and ranking different fuels. There were a number of studies on EROI three decades ago but relatively little work since. Now there is a whole new interest in EROI as fuels get increasingly expensive and as we attempt to weigh alternative energies against traditional ones. This special volume brings together a whole series of high quality new studies on EROI, as well as many papers that struggle with the meaning of changing EROI and its impact on our economy. One overall conclusion is that the quality of fuels is at least as important in our assessment as is the quantity. I argue that many of the contemporary changes in our economy are related directly to changing EROI as our premium fuels are increasingly depleted.
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Human society is now at the beginning of a transition from fossil-fuel based primary energy sources to a mixture of renewable and nuclear based energy sources which have a lower Energy Return On Energy Invested (EROEI) than the older fossil based sources. This

Human society is now at the beginning of a transition from fossil-fuel based primary energy sources to a mixture of renewable and nuclear based energy sources which have a lower Energy Return On Energy Invested (EROEI) than the older fossil based sources. This paper examines the evolution of total energy demand during this transition for a highly idealized energy economy. A simple model is introduced in which the net useful energy output required to operate an economy is assumed to remain fixed while the lower EROEI source gradually replaces the older higher EROEI primary energy source following a logistics substitution model. The results show that, for fixed net useful energy output, total energy demand increases as the ratio EROEInew/EROEIold decreases; total energy demand diverges as EROEInew approaches unity, indicating that the system must collapse in this limit.
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The two most frequently quantified metrics of net energy analysis–the energy return on (energy) investment and the energy payback period–do not capture the growth rate potential of an energy supply infrastructure. This is because the analysis underlying these metrics is essentially static–all energy

The two most frequently quantified metrics of net energy analysis–the energy return on (energy) investment and the energy payback period–do not capture the growth rate potential of an energy supply infrastructure. This is because the analysis underlying these metrics is essentially static–all energy inputs and outputs are treated the same, regardless of where they occur in the life cycle of the infrastructure. We develop a dynamic energy analysis framework to model the growth potential of alternative electricity supply infrastructures. An additional figure of merit, the infrastructure doubling time, is introduced. This metric highlights the critical importance of the time phasing of the initial energy investment for emplacing a given infrastructure, as opposed to the ongoing O&M energy expenditures, for the infrastructure’s growth potential. The doubling time metric also captures the influence of capacity factor, licensing and construction time lags.
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Agriculture is the largest sector of Pakistan’s economy, contributing almost 22% to the GDP and employing almost 45% of the total labor force. The two largest food crops, wheat and rice, contribute 3.1% and 1.4% to the GDP, respectively. The objective of this

Agriculture is the largest sector of Pakistan’s economy, contributing almost 22% to the GDP and employing almost 45% of the total labor force. The two largest food crops, wheat and rice, contribute 3.1% and 1.4% to the GDP, respectively. The objective of this research was to calculate the energy return on investment (EROI) of these crops on a national scale from 1999 to 2009 to understand the size of various energy inputs and to discuss their contributions to the energy output. Energy inputs accounted for within the cropping systems included seed, fertilizer, pesticide, human labor, tractor diesel, irrigation pump electricity and diesel, the transport of fertilizer and pesticide, and the embodied energy of tractors and irrigation pumps. The largest per-hectare energy inputs to wheat were nitrogen fertilizer (52.6%), seed (17.9%), and tractor diesel (9.1%). For rice, the largest per-hectare energy inputs were nitrogen fertilizer (32%), tube well diesel (19.8%), and pesticide (17.6%). The EROI of wheat showed a gradual downward trend between 2000 and 2006 of 21.3%. The trend was erratic thereafter. Overall, it ranged from 2.7 to 3.4 with an average of 2.9 over the 11-year study period. The overall trend was fairly consistent compared to that of rice which ranged between 3.1 and 4.9, and averaged 3.9. Rice’s EROI dipped sharply in 2002, was erratic, and remained below four until 2007. It rose sharply after that. As energy inputs increased, wheat outputs increased, but rice outputs decreased slightly. Rice responded to inputs with greater output and an increase in EROI. The same was not true for wheat, which showed little change in EROI in the face of increasing inputs. This suggests that additional investments of energy in rice production are not improving yields but for wheat, these investments are still generating benefits. The analysis shows quantitatively how fossil energy is a key driver of the Pakistani agricultural system as it traces direct and indirect energy inputs to two major food crops.
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In China there has been considerable discussion of how one should express the efficiency of energy conversion and production. Energy return on investment (EROI) can be useful for this because its methodology is based on outputs and inputs. Unfortunately, similar to the rest

In China there has been considerable discussion of how one should express the efficiency of energy conversion and production. Energy return on investment (EROI) can be useful for this because its methodology is based on outputs and inputs. Unfortunately, similar to the rest of the world, most of the data available for assessing energy gains and costs for oil and gas in China has to be derived from economic costs and revenues for oil fields. In this paper we derive a first EROI for China based on using this approach and the existing data for production of crude oil and natural gas for the Daqing oil field, the largest oil field in China. We estimate that its EROIstnd expressed as heat equivalent was 10:1 in 2001 but has declined to 6.5:1 in 2009. Based on this trend we project that the EROIstnd will decline to 4.7:1 in 2015, and the net energy from the field will be decreasing substantially. The calculations have some errors because of incomplete data, and if various externalities are taken into account, the EROI of this oil field would be lower than our present estimates. The trends of EROI and net energy suggest that the Daqing oil field will face more difficulty in the future which can not be overcome by government fiat.
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The two methods of processing synthetic crude from organic marlstone in demonstration or small-scale commercial status in the U.S. are in situ extraction and surface retorting. The considerable uncertainty surrounding the technological characterization, resource characterization, and choice of the system boundary for oil

The two methods of processing synthetic crude from organic marlstone in demonstration or small-scale commercial status in the U.S. are in situ extraction and surface retorting. The considerable uncertainty surrounding the technological characterization, resource characterization, and choice of the system boundary for oil shale operations indicate that oil shale is only a minor net energy producer if one includes internal energy (energy in the shale that is used during the process) as an energy cost. The energy return on investment (EROI) for either of these methods is roughly 1.5:1 for the final fuel product. The inclusions or omission of internal energy is a critical question. If only external energy (energy diverted from the economy to produce the fuel) is considered, EROI appears to be much higher. In comparison, fuels produced from conventional petroleum show overall EROI of approximately 4.5:1. “At the wellhead” EROI is approximately 2:1 for shale oil (again, considering internal energy) and 20:1 for petroleum. The low EROI for oil shale leads to a significant release of greenhouse gases. The large quantities of energy needed to process oil shale, combined with the thermochemistry of the retorting process, produce carbon dioxide and other greenhouse gas emissions. Oil shale unambiguously emits more greenhouse gases than conventional liquid fuels from crude oil feedstocks by a factor of 1.2 to 1.75. Much of the discussion regarding the EROI for oil shale should be regarded as preliminary or speculative due to the very small number of operating facilities that can be assessed.
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We model the low frequency electrical heating of submarine methane hydrate deposits located at depths between 1000 and 1500 m, and determine the energy return on energy invested (EROI) for this process. By means of the enthalpy method, we calculate the time-dependent heating

We model the low frequency electrical heating of submarine methane hydrate deposits located at depths between 1000 and 1500 m, and determine the energy return on energy invested (EROI) for this process. By means of the enthalpy method, we calculate the time-dependent heating of these deposits under applied electrical power supplied to a cylindrical heater located at the center of the reservoir and at variable depths. The conversion of the produced water to steam is avoided by limiting the heater temperature. We calculate the volume of methane hydrate that will melt and the energy equivalent of the gas thus generated. The partial energy efficiency of this heating process is obtained as the ratio of the gas equivalent energy to the applied electrical energy. We obtain EROI values in the range of 4 to 5, depending on the location of the heater. If the methane gas is used to generate the electrical energy required in the heating (in processes with a 33% efficiency), the effective EROI of the process falls in the range of 4/3 to 5/3.
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Oil has played a crucial role in the United States’ continued but increasingly tenuous economic prosperity. The continued availability of cheap, high energy return on investment (EROI) oil, however, is increasingly in doubt. If cheap oil is increasingly constrained, how might that impact

Oil has played a crucial role in the United States’ continued but increasingly tenuous economic prosperity. The continued availability of cheap, high energy return on investment (EROI) oil, however, is increasingly in doubt. If cheap oil is increasingly constrained, how might that impact the American psychological sense of personal and national well-being? We employ general systems theory and certain key paradigms from psychology and sociology to predict the possible societal response to global peak oil and the declining EROI of whatever oil is produced. Based on these frameworks, the following three defense mechanisms seem likely to be employed by individuals and groups within society if and when confronted with stresses associated with declining oil availability. These are: denial of one’s passive helpless state, desire to establish a scapegoat, and arousal of affiliative needs and increased subgrouping. A group’s “survival” is a function of its unified sense of direction and the stability of necessary interdependencies and linkages. We suggest that the ability of the U.S. society, taken as a whole, to adapt to the stresses derived from the declining EROI of oil will increase during periods of moderate stress, and then decline after reaching its maximum ability to cope with stress. The integrity of interdependencies and linkages—power, communication, affect, and goals—must be preserved for continued social unity. Americans will need to acknowledge the reality of biophysical constraints if they are to adapt to the coming energy crisis.
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Canada was the world’s third largest natural gas producer in 2008, with 98% of its gas being produced by conventional, tight gas, and coal bed methane wells in Western Canada. Natural gas production in Western Canada peaked in 2001 and remained nearly flat

Canada was the world’s third largest natural gas producer in 2008, with 98% of its gas being produced by conventional, tight gas, and coal bed methane wells in Western Canada. Natural gas production in Western Canada peaked in 2001 and remained nearly flat until 2006 despite more than quadrupling the drilling rate. Canada seems to be one of many counter examples to the idea that oil and gas production can rise with sufficient investment. This study calculated the Energy Return on Energy Invested and Net Energy of conventional natural gas and oil production in Western Canada by a variety of methods to explore the energy dynamics of the peaking process. All these methods show a downward trend in EROI during the last decade. Natural gas EROI fell from 38:1 in 1993 to 15:1 at the peak of drilling in 2005. The drilling intensity for natural gas was so high that net energy delivered to society peaked in 2000–2002, while production did not peak until 2006. The industry consumed all the extra energy it delivered to maintain the high drilling effort. The inability of a region to increase net energy may be the best definition of peak production. This increase in energy consumption reduces the total energy provided to society and acts as a contracting pressure on the overall economy as the industry consumes greater quantities of labor, steel, concrete and fuel. It appears that energy production from conventional oil and gas in Western Canada has peaked and entered permanent decline.
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Norwegian oil and gas fields are relatively new and of high quality, which has led, during recent decades, to very high profitability both financially and in terms of energy production. One useful measure for profitability is Energy Return on Investment, EROI. Our analysis

Norwegian oil and gas fields are relatively new and of high quality, which has led, during recent decades, to very high profitability both financially and in terms of energy production. One useful measure for profitability is Energy Return on Investment, EROI. Our analysis shows that EROI for Norwegian petroleum production ranged from 44:1 in the early 1990s to a maximum of 59:1 in 1996, to about 40:1 in the latter half of the last decade. To compare globally, only very few, if any, resources show such favorable EROI values as those found in the Norwegian oil and gas sector. However, the declining trend in recent years is most likely due to ageing of the fields whereas varying drilling intensity might have a smaller impact on the net energy gain of the fields. We expect the EROI of Norwegian oil and gas production to deteriorate further as the fields become older. More energy-intensive production techniques will gain in importance.
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Declining energy return on investment (EROI) of a society’s available energy sources can lead to both crisis and opportunity for positive social change. The implications of declining EROI for human wellbeing are complex and open to interpretation. There are many reasons why frugal

Declining energy return on investment (EROI) of a society’s available energy sources can lead to both crisis and opportunity for positive social change. The implications of declining EROI for human wellbeing are complex and open to interpretation. There are many reasons why frugal living and an energy diet could be beneficial. A measure of wellbeing or welfare gained per unit of energy expended (WROEI) is proposed. A threshold is hypothesized for the relation between energy consumption and wellbeing. The paper offers a biophysical-based social science explanation for both the negative and positive possible implications of declining EROI. Two sets of future scenarios based on environmental and economic trends are described. Six types of social change activism are considered essential if the positives of declining EROI are to balance or exceed the negatives.
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The purpose of this paper is to calculate the energy return on financial investment (EROFI) of oil and gas production in the ultra-deepwater Gulf of Mexico (GoM) in 2009 and for the estimated oil reserves of the Macondo Prospect (Mississippi Canyon Block 252).

The purpose of this paper is to calculate the energy return on financial investment (EROFI) of oil and gas production in the ultra-deepwater Gulf of Mexico (GoM) in 2009 and for the estimated oil reserves of the Macondo Prospect (Mississippi Canyon Block 252). We also calculated a preliminary Energy Return on Investment (EROI) based on published energy intensity ratios including a sensitivity analysis using a range of energy intensity ratios (7 MJ/$, 12 MJ/$, and 18 MJ/$). The EROFI for ultra-deepwater oil and gas at the well-head, ranged from 0.019 to 0.022 barrels (BOE), or roughly 0.85 gallons, per dollar. Our estimates of EROI for 2009 ultra-deepwater oil and natural gas at the well-head ranged from 7–22:1. The independently-derived EROFI of the Macondo Prospect oil reserves ranged from 0.012 to 0.0071 barrels per dollar (i.e., $84 to $140 to produce a barrel) and EROI ranged from 4–16:1, related to the energy intensity ratio used to quantify costs. We believe that the lower end of these EROI ranges (i.e., 4 to 7:1) is more accurate since these values were derived using energy intensities averaged across the entire domestic oil and gas industry. Time series of the financial and preliminary EROI estimates found in this study suggest that the extraction costs of ultra-deepwater energy reserves in the GoM come at increasing energetic and economic cost to society.
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The energy cost of drilling a natural gas well has never been publicly addressed in terms of the actual fuels and energy required to generate the physical materials consumed in construction. Part of the reason for this is that drilling practices are typically

The energy cost of drilling a natural gas well has never been publicly addressed in terms of the actual fuels and energy required to generate the physical materials consumed in construction. Part of the reason for this is that drilling practices are typically regarded as proprietary; hence the required information is difficult to obtain. We propose that conventional tight gas wells that have marginal production characteristics provide a baseline for energy return on energy invested (EROI) analyses. To develop an understanding of baseline energy requirements for natural gas extraction, we examined production from a mature shallow gas field composed of vertical wells in Pennsylvania and materials used in the drilling and completion of individual wells. The data were derived from state maintained databases and reports, personal experience as a production geologist, personal interviews with industry representatives, and literature sources. We examined only the “upstream” energy cost of providing gas and provide a minimal estimate of energy cost because of uncertainty about some inputs. Of the materials examined, steel and diesel fuel accounted for more than two-thirds of the energy cost for well construction. Average energy cost per foot for a tight gas well in Indiana County is 0.59 GJ per foot. Available production data for this natural gas play was used to calculate energy return on energy invested ratios (EROI) between 67:1 and 120:1, which depends mostly on the amount of materials consumed, drilling time, and highly variable production. Accounting for such inputs as chemicals used in well treatment, materials used to construct drill bits and drill pipe, post-gathering pipeline construction, and well completion maintenance would decrease EROI by an unknown amount. This study provides energy constraints at the single-well scale for the energy requirements for drilling in geologically simple systems. The energy and monetary costs of wells from Indiana County, Pennsylvania are useful for constructing an EROI model of United States natural gas production, which suggests a peak in the EROI of gas production, has already occurred twice in the past century.
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The main objective of this manuscript is to provide a formal methodology, structure, and nomenclature for EROI analysis that is both consistent, so that all EROI numbers across various processes can be compared, and also flexible, so that changes or additions to the

The main objective of this manuscript is to provide a formal methodology, structure, and nomenclature for EROI analysis that is both consistent, so that all EROI numbers across various processes can be compared, and also flexible, so that changes or additions to the universal formula can focus analyses on specific areas of concern. To accomplish this objective we address four areas that are of particular interest within EROI analysis: (1) boundaries of the system under analysis, (2) energy quality corrections, (3) energy-economic conversions, and (4) alternative EROI statistics. Lastly, we present step-by-step instructions outlining how to perform an EROI analysis.
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A more objective method for measuring the energy needs of businesses, System Energy Assessment (SEA), measures the combined impacts of material supply chains and service supply chains, to assess businesses as whole self-managing net-energy systems. The method is demonstrated using a model Wind

A more objective method for measuring the energy needs of businesses, System Energy Assessment (SEA), measures the combined impacts of material supply chains and service supply chains, to assess businesses as whole self-managing net-energy systems. The method is demonstrated using a model Wind Farm, and defines a physical measure of their energy productivity for society (EROI-S), a ratio of total energy delivered to total energy expended. Energy use records for technology and proxy measures for clearly understood but not individually recorded energy uses for services are combined for a whole system estimate of consumption required for production. Current methods count only energy needs for technology. Business services outsource their own energy needs to operate, leaving no traceable record. That uncounted business energy demand is often 80% of the total, an amount of “dark energy” hidden from view, discovered by finding the average energy estimated needs for businesses far below the world average energy consumed per dollar of GDP. Presently for lack of information the energy needs of business services are counted to be “0”. Our default assumption is to treat them as “average”. The result is a hard measure of total business demand for energy services, a “Scope 4” energy use or GHG impact assessment. Counting recorded energy uses and discounting unrecorded ones misrepresents labor intensive work as highly energy efficient. The result confirms a similar finding by Hall et al. in 1981 [1]. We use exhaustive search for what a business needs to operate as a whole, tracing internal business relationships rather than energy data, to locate its natural physical boundary as a working unit, and so define a business as a physical rather than statistical subject of scientific study. See also online resource materials and notes [2].
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Most estimates of energy-return-on-investment (EROI) are “static”. They determine the amount of energy produced by a particular energy technology at a particular location at a particular time. Some “dynamic” estimates are also made that track the changes in EROI of a particular resource

Most estimates of energy-return-on-investment (EROI) are “static”. They determine the amount of energy produced by a particular energy technology at a particular location at a particular time. Some “dynamic” estimates are also made that track the changes in EROI of a particular resource over time. Such approaches are “bottom-up”. This paper presents a conceptual framework for a “top-down” dynamic function for the EROI of an energy resource. This function is constructed from fundamental theoretical considerations of energy technology development and resource depletion. Some empirical evidence is given as corroboration of the shape of the function components.
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Oil and gas are the main sources of energy in the United States. Part of their appeal is the high Energy Return on Energy Investment (EROI) when procuring them. We assessed data from the United States Bureau of the Census of Mineral Industries,

Oil and gas are the main sources of energy in the United States. Part of their appeal is the high Energy Return on Energy Investment (EROI) when procuring them. We assessed data from the United States Bureau of the Census of Mineral Industries, the Energy Information Administration (EIA), the Oil and Gas Journal for the years 1919–2007 and from oil analyst Jean Laherrere to derive EROI for both finding and producing oil and gas. We found two general patterns in the relation of energy gains compared to energy costs: a gradual secular decrease in EROI and an inverse relation to drilling effort. EROI for finding oil and gas decreased exponentially from 1200:1 in 1919 to 5:1 in 2007. The EROI for production of the oil and gas industry was about 20:1 from 1919 to 1972, declined to about 8:1 in 1982 when peak drilling occurred, recovered to about 17:1 from 1986–2002 and declined sharply to about 11:1 in the mid to late 2000s. The slowly declining secular trend has been partly masked by changing effort: the lower the intensity of drilling, the higher the EROI compared to the secular trend. Fuel consumption within the oil and gas industry grew continuously from 1919 through the early 1980s, declined in the mid-1990s, and has increased recently, not surprisingly linked to the increased cost of finding and extracting oil.
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This study explores the impact of oil depletion on the energetic efficiency of oil extraction and refining in California. These changes are measured using energy return ratios (such as the energy return on investment, or EROI). I construct a time-varying first-order process model

This study explores the impact of oil depletion on the energetic efficiency of oil extraction and refining in California. These changes are measured using energy return ratios (such as the energy return on investment, or EROI). I construct a time-varying first-order process model of energy inputs and outputs of oil extraction. The model includes factors such as oil quality, reservoir depth, enhanced recovery techniques, and water cut. This model is populated with historical data for 306 California oil fields over a 50 year period. The model focuses on the effects of resource quality decline, while technical efficiencies are modeled simply. Results indicate that the energy intensity of oil extraction in California increased significantly from 1955 to 2005. This resulted in a decline in the life-cycle EROI from 6.5 to 3.5 (measured as megajoules (MJ) delivered to final consumers per MJ primary energy invested in energy extraction, transport, and refining). Most of this decline in energy returns is due to increasing need for steam-based thermal enhanced oil recovery, with secondary effects due to conventional resource depletion (e.g., increased water cut).
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For many reasons, including environmental impacts and the peaking and depletion of the highest grades of fossil energy, it is very important to have sound methods for the evaluation of energy technologies and the profitability of the businesses that utilize them. In this

For many reasons, including environmental impacts and the peaking and depletion of the highest grades of fossil energy, it is very important to have sound methods for the evaluation of energy technologies and the profitability of the businesses that utilize them. In this paper we derive relations among the biophysical characteristic of an energy resource in relation to the businesses and technologies that exploit them. These relations include the energy return on energy investment (EROI), the price of energy, and the profit of an energy business. Our analyses show that EROI and the price of energy are inherently inversely related such that as EROI decreases for depleting fossil fuel production, the corresponding energy prices increase dramatically. Using energy and financial data for the oil and gas production sector, we demonstrate that the equations sufficiently describe the fundamental trends between profit, price, and EROI. For example, in 2002 an EROI of 11:1 for US oil and gas translates to an oil price of 24 $2005/barrel at a typical profit of 10%. This work sets the stage for proper EROI and price comparisons of individual fossil and renewable energy businesses as well as the electricity sector as a whole. Additionally, it presents a framework for incorporating EROI into larger economic systems models.
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The authors of this paper have been involved in contentious discussion of the EROI of biomass-based ethanol. This contention has undermined, in the minds of some, the utility of EROI for assessing fuels. This paper seeks to understand the reasons for the divergent

The authors of this paper have been involved in contentious discussion of the EROI of biomass-based ethanol. This contention has undermined, in the minds of some, the utility of EROI for assessing fuels. This paper seeks to understand the reasons for the divergent results.
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